The source matrix should be continuous, otherwise reallocation and data copying is performed. The function chooses an operation mode depending on the flags, size, and channel count of the source matrix:

If the source matrix is complex and the output is not specified as real, the destination matrix is complex and has the dft_size size and CV_32FC2 type. The destination matrix contains a full result of the DFT (forward or inverse).

If the source matrix is complex and the output is specified as real, the function assumes that its input is the result of the forward transform (see the next item). The destination matrix has the dft_size size and CV_32FC1 type. It contains the result of the inverse DFT.

If the source matrix is real (its type is CV_32FC1 ), forward DFT is performed. The result of the DFT is packed into complex ( CV_32FC2 ) matrix. So, the width of the destination matrix is dft_size.width/2+1 . But if the source is a single column, the height is reduced instead of the width.

You can use field user_block_size to set specific block size for gpu::convolve() function. If you leave its default value Size(0,0) then automatic estimation of block size will be used (which is optimized for speed). By varying user_block_size you can reduce memory requirements at the cost of speed.

You can use field user_block_size to set specific block size for gpu::matchTemplate() function. If you leave its default value Size(0,0) then automatic estimation of block size will be used (which is optimized for speed). By varying user_block_size you can reduce memory requirements at the cost of speed.

dstOrder – Integer array describing how channel values are permutated. The n-th entry of the array contains the number of the channel that is stored in the n-th channel of the output image. E.g. Given an RGBA image, aDstOrder = [3,2,1,0] converts this to ABGR channel order.

stream – Stream for the asynchronous version.

The methods support arbitrary permutations of the original channels, including replication.

search_window – Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. Affect performance linearly: greater search_window - greater denoising time. Recommended value 21 pixels

block_size – Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels

stream – Stream for the asynchronous invocations.

This function expected to be applied to grayscale images. For colored images look at FastNonLocalMeansDenoising::labMethod.

float – The same as h but for color components. For most images value equals 10 will be enought to remove colored noise and do not distort colors

search_window – Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. Affect performance linearly: greater search_window - greater denoising time. Recommended value 21 pixels

block_size – Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels

stream – Stream for the asynchronous invocations.

The function converts image to CIELAB colorspace and then separately denoise L and AB components with given h parameters using FastNonLocalMeansDenoising::simpleMethod function.

circles – Output vector of found circles. Each vector is encoded as a 3-element floating-point vector .

method – Detection method to use. Currently, the only implemented method is CV_HOUGH_GRADIENT , which is basically 21HT , described in [Yuen90].

dp – Inverse ratio of the accumulator resolution to the image resolution. For example, if dp=1 , the accumulator has the same resolution as the input image. If dp=2 , the accumulator has half as big width and height.

minDist – Minimum distance between the centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed.

cannyThreshold – The higher threshold of the two passed to the gpu::Canny() edge detector (the lower one is twice smaller).

votesThreshold – The accumulator threshold for the circle centers at the detection stage. The smaller it is, the more false circles may be detected.

minRadius – Minimum circle radius.

maxRadius – Maximum circle radius.

maxCircles – Maximum number of output circles.

buf – Optional buffer to avoid extra memory allocations (for many calls with the same sizes).